Data-dependent acquisition (also referred to, in various commercial implementations, as Information Dependent Acquisition (IDA), Data Directed Analysis (DDA), and AUTO MS/MS) is a valuable and widely-used tool in the mass spectrometry art, particularly for the analysis of complex samples. Generally described, data-dependent acquisition involves using data derived from an experimentally-acquired mass spectrum in an “on-the-fly” manner to direct the subsequent operation of a mass spectrometer; for example, a mass spectrometer may be switched between MS and MS/MS scan modes upon detection of an ion species of potential interest. Utilization of data-dependent acquisition methods in a mass spectrometer provides the ability to make automated, real-time decisions in order to maximize the useful information content of the acquired data, thereby avoiding or reducing the need to perform multiple chromatographic runs or injections of the analyte sample. These methods can be tailored for specific desired objectives, such as enhancing the number of peptide identifications from the analysis of a complex mixture of peptides derived from a biological sample.
Data-dependent acquisition methods may be characterized as having one or more input criteria, and one or more output actions. The input criteria employed for conventional data-dependent methods are generally based on parameters such as intensity, intensity pattern, mass window, mass difference (neutral loss), mass-to-charge (m/z) inclusion and exclusion lists, and product ion mass. The input criteria are employed to select one or more ion species that satisfy the criteria. The selected ion species are then subjected to an output action (examples of which include performing MS/MS or MSn analysis and/or high-resolution scanning). In one instance of a typical data-dependent experiment, a group of ions are mass analyzed, and ion species having mass spectral intensities exceeding a specified threshold are subsequently selected as precursor ions for MS/MS analysis, which may involve operations of isolation, dissociation of the precursor ions, and mass analysis of the product ions.
The growing use of mass spectrometry for the analysis of peptides, proteins, and other biomolecules has led researchers to develop new dissociation techniques, including pulsed-q dissociation (PQD) and electron transfer dissociation (ETD), that provide additional and/or different informational content relative to conventional techniques. However, the data-dependent acquisition methods described in the prior art have been largely limited to use with a single, conventional dissociation mode. While certain references in the prior art (see, e.g., LeBlanc et al., “Unique Scanning Capabilities of a New Hybrid Linear Ion Trap Mass Spectrometer (Q Trap) Used for High Sensitivity Proteomics Applications, Proteomics, vol. 3, pp. 859-869 (2003)) have described using data-dependent methods to automatically adjust dissociation parameters such as collision energy, there remains a need for novel data-dependent acquisition methods that can be employed with the recently developed advanced dissociation techniques to more fully exploit the opportunities for acquiring enhanced informational content.